Citation

Zhang Y, Liu T, Bai Q, Shao W, Wang Q. Transp. Res. F Traffic Psychol. Behav. 2018; 54: 96-109.

Copyright

(Copyright © 2018, Elsevier Publishing)

DOI

10.1016/j.trf.2018.01.019

PMID

unavailable

Abstract

Road safety has become a major public issue in China. This study collected a total of 396 road traffic accident cases that occurred in 28 provinces from 1985 to 2014 in China. The type of vehicles involved in the accidents includes cargo vehicles (126), passenger vehicles (253), dangerous chemicals transport vehicles (128), and cars (9). A new systems approach that integrates the causal categories framework based on the human factor analysis and classification system (HFACS) and the contributory factor interactions model (CFIM) was applied to conduct analysis of road traffic accidents to determine whether systems approaches should be used during road accident analysis efforts. The analysis of results leads to the following conclusions. (i) According to the causal categories framework based on HFACS, the frequency of "unsafe behaviours" is highest at the category level; the frequency of "violations" is the highest at the subcategory level. "Overloading/overcrowding," "speeding," "failed to provide supervision," and "fatigue driving" should receive attention at the special indicator level. (ii) The new systems-based method that integrated the HFACS and the CFIM, which highlights the interactions between all levels of the causal categories, is a suitable method to analyse road traffic accidents. (iii) All latent categories, including "outside factors," "organizational influences," "unsafe supervision," and "preconditions for unsafe behaviours," can affect "unsafe behaviours"; "outside factors," "organizational influences," "unsafe supervision," and "preconditions for unsafe behaviours" can influence each other. These interactions have not been quantitatively examined in previous studies. The findings of this study also demonstrate that the OR is a suitable technique to quantitatively examine the interactions among contributory factors.

Language: en

Keywords

Accidents analysis; Contributory factor interactions model (CFIM); Human factor analysis and classification system (HFACS); Road traffic accidents; Systems-based method